Genetic algorithms + data structures = evolution programs - Info and Reading Options
By Zbigniew Michalewicz
"Genetic algorithms + data structures = evolution programs" was published by Springer-Verlag in 1996 - Berlin, it has 387 pages and the language of the book is English.
“Genetic algorithms + data structures = evolution programs” Metadata:
- Title: ➤ Genetic algorithms + data structures = evolution programs
- Author: Zbigniew Michalewicz
- Language: English
- Number of Pages: 387
- Publisher: Springer-Verlag
- Publish Date: 1996
- Publish Location: Berlin
“Genetic algorithms + data structures = evolution programs” Subjects and Themes:
- Subjects: ➤ Computer algorithms - Computer programs - Data structures (Computer science) - Evolutionary programming (Computer science) - Genetic algorithms - Logiciels - Optimisation numérique - Saisie des données (Informatique) - Problème transport - Algorithmes - Algorithme génétique - Partitionnement - Genetischer Algorithmus - Computadoras digitales (Programación) - Structures de données (Informatique) - Algorithmique - Estructura de datos (Ciencia de la computación) - Ordonnancement - Voyageur commerce - Structure donnée - Programowanie ewolucyjne - Algorytmy genetyczne - Optymalizacja - Struktury danych (informatyka) - Numerical analysis - Algorithms - Artificial intelligence - Software engineering - Operations research - Computer science - Qa76.9.a43 m53 1994 - 005.1
Edition Specifications:
- Pagination: xx, 387 p. :
Edition Identifiers:
- The Open Library ID: OL811129M - OL47602W
- Online Computer Library Center (OCLC) ID: 33897934
- Library of Congress Control Number (LCCN): 95048027
- ISBN-13: 9783540606765
- ISBN-10: 3540606769
- All ISBNs: 3540606769 - 9783540606765
AI-generated Review of “Genetic algorithms + data structures = evolution programs”:
"Genetic algorithms + data structures = evolution programs" Description:
The Open Library:
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The aim of this book is to talk about the field of evolutionary computation in simple terms, and discuss the simplicity and elegance of its methods on many interesting test cases. The book may serve as a guide to writing an evolution program, and to making this an enjoyable experience. It is self-contained and the only prerequisite is basic undergraduate mathematics. Aimed at researchers, practitioners, and graduate students, it may serve as a text for advanced courses in computer science and artificial intelligence, operations research, and engineering. This third edition has been substantially revised and extended. Three new chapters discuss the recent paradigm of genetic programming, heuristic methods and constraint handling, and current directions of research. Additional appendices contain test functions for experiments with evolutionary techniques and discuss possible projects for use in a project-oriented course.
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